aiworkhub_dashboard_settings_update

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden and does so well: it labels the tool as USER WRITE, describes optimistic revision locking, notes atomic persistence on revision match, and discloses side effects such as starting/stopping Source Graph and initializing the context graph schema. These are exactly the mutation and concurrency traits an agent needs beyond the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the write/atomicity warning, then moves directly into routing guidance and behavioral effects. Every sentence adds actionable information, with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter mutation tool with full schema coverage and an output schema, the description supplies the missing operational context: concurrency expectations, atomicity, side effects, and sibling alternatives. Nothing essential for correct invocation is left out.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds useful meaning by naming example feature keys (source_graph, context_graph) and tying them to observable side effects, though it does not enumerate all valid keys or explain the changes object beyond those examples.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a precise verb and resource: atomically update repository-local feature switches. It explicitly distinguishes top-level feature switches from language/model routing switches and names the sibling tools to use instead, so an agent can route correctly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives direct usage guidance: use this tool to toggle top-level features like source_graph or context_graph, inspect current switches and revision with aiworkhub_dashboard_settings first, and use other update tools for language or model routing switches. The alternatives and selection conditions are explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.